* feat: add configurable log level and token usage tracking
- Add `log_level` config to control deerflow module log level, synced
to LangGraph Server via serve.sh `--server-log-level`
- Add `token_usage.enabled` config with TokenUsageMiddleware that logs
input/output/total tokens per LLM call from usage_metadata
- Add .omc/ to .gitignore
* fix: use info level for token usage logs since feature has its own toggle
* fix: sort imports to pass lint check
---------
Co-authored-by: greatmengqi <chenmengqi.0376@bytedance.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
Add GuardrailMiddleware that evaluates every tool call before execution.
Three provider options: built-in AllowlistProvider (zero deps), OAP passport
providers (open standard), or custom providers loaded by class path.
- GuardrailProvider protocol with GuardrailRequest/Decision dataclasses
- GuardrailMiddleware (AgentMiddleware, position 5 in chain)
- AllowlistProvider for simple deny/allow by tool name
- GuardrailsConfig (Pydantic singleton, loaded from config.yaml)
- 25 tests covering allow/deny, fail-closed/open, async, GraphBubbleUp
- Comprehensive docs at backend/docs/GUARDRAILS.md
Closes#1213
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* feat(tools): add tool_search for deferred MCP tool loading
When multiple MCP servers are enabled, total tool count can exceed 30-50,
causing context bloat and degraded tool selection accuracy. This adds a
deferred tool loading mechanism controlled by `tool_search.enabled` config.
- Add ToolSearchConfig with single `enabled` field
- Add DeferredToolRegistry with regex search (select:, +keyword, keyword)
- Add tool_search tool returning OpenAI-compatible function JSON
- Add DeferredToolFilterMiddleware to hide deferred schemas from bind_tools
- Add <available-deferred-tools> section to system prompt
- Enable MCP tool_name_prefix to prevent cross-server name collisions
- Add 34 unit tests covering registry, tool, prompt, and middleware
* fix: reset stale deferred registry and bump config_version
- Reset deferred registry upfront in get_available_tools() to prevent
stale tool entries when MCP servers are disabled between calls
- Bump config_version to 2 for new tool_search config field
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(tests): mock get_app_config in prompt section tests for CI
CI has no config.yaml, causing TestDeferredToolsPromptSection to fail
with FileNotFoundError. Add autouse fixture to mock get_app_config.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* refactor: extract shared utils to break harness→app cross-layer imports
Move _validate_skill_frontmatter to src/skills/validation.py and
CONVERTIBLE_EXTENSIONS + convert_file_to_markdown to src/utils/file_conversion.py.
This eliminates the two reverse dependencies from client.py (harness layer)
into gateway/routers/ (app layer), preparing for the harness/app package split.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* refactor: split backend/src into harness (deerflow.*) and app (app.*)
Physically split the monolithic backend/src/ package into two layers:
- **Harness** (`packages/harness/deerflow/`): publishable agent framework
package with import prefix `deerflow.*`. Contains agents, sandbox, tools,
models, MCP, skills, config, and all core infrastructure.
- **App** (`app/`): unpublished application code with import prefix `app.*`.
Contains gateway (FastAPI REST API) and channels (IM integrations).
Key changes:
- Move 13 harness modules to packages/harness/deerflow/ via git mv
- Move gateway + channels to app/ via git mv
- Rename all imports: src.* → deerflow.* (harness) / app.* (app layer)
- Set up uv workspace with deerflow-harness as workspace member
- Update langgraph.json, config.example.yaml, all scripts, Docker files
- Add build-system (hatchling) to harness pyproject.toml
- Add PYTHONPATH=. to gateway startup commands for app.* resolution
- Update ruff.toml with known-first-party for import sorting
- Update all documentation to reflect new directory structure
Boundary rule enforced: harness code never imports from app.
All 429 tests pass. Lint clean.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* chore: add harness→app boundary check test and update docs
Add test_harness_boundary.py that scans all Python files in
packages/harness/deerflow/ and fails if any `from app.*` or
`import app.*` statement is found. This enforces the architectural
rule that the harness layer never depends on the app layer.
Update CLAUDE.md to document the harness/app split architecture,
import conventions, and the boundary enforcement test.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: add config versioning with auto-upgrade on startup
When config.example.yaml schema changes, developers' local config.yaml
files can silently become outdated. This adds a config_version field and
auto-upgrade mechanism so breaking changes (like src.* → deerflow.*
renames) are applied automatically before services start.
- Add config_version: 1 to config.example.yaml
- Add startup version check warning in AppConfig.from_file()
- Add scripts/config-upgrade.sh with migration registry for value replacements
- Add `make config-upgrade` target
- Auto-run config-upgrade in serve.sh and start-daemon.sh before starting services
- Add config error hints in service failure messages
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix comments
* fix: update src.* import in test_sandbox_tools_security to deerflow.*
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: handle empty config and search parent dirs for config.example.yaml
Address Copilot review comments on PR #1131:
- Guard against yaml.safe_load() returning None for empty config files
- Search parent directories for config.example.yaml instead of only
looking next to config.yaml, fixing detection in common setups
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: correct skills root path depth and config_version type coercion
- loader.py: fix get_skills_root_path() to use 5 parent levels (was 3)
after harness split, file lives at packages/harness/deerflow/skills/
so parent×3 resolved to backend/packages/harness/ instead of backend/
- app_config.py: coerce config_version to int() before comparison in
_check_config_version() to prevent TypeError when YAML stores value
as string (e.g. config_version: "1")
- tests: add regression tests for both fixes
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix: update test imports from src.* to deerflow.*/app.* after harness refactor
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* Add MiniMax as an OpenAI-compatible model provider
MiniMax offers high-performance LLMs (M2.5, M2.5-highspeed) with
204K context windows. This commit adds MiniMax as a selectable
provider in the configuration system.
Changes:
- Add MiniMax to SUPPORTED_MODELS with model definitions
- Add MiniMax provider configuration in conf/config.yaml
- Update documentation with MiniMax setup instructions
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Update README to remove MiniMax API details
Removed mention of MiniMax API usage and configuration examples.
---------
Co-authored-by: octo-patch <octo-patch@users.noreply.github.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* Refactor sandbox state management and improve Docker integration
- Removed FileSandboxStateStore and SandboxStateStore classes for a cleaner architecture.
- Enhanced LocalContainerBackend to handle port allocation retries and introduced environment variable support for sandbox host configuration.
- Updated Paths class to include host_base_dir for Docker volume mounts and ensured proper permissions for sandbox directories.
- Modified ExtensionsConfig to improve error handling when loading configuration files and adjusted environment variable resolution.
- Updated sandbox configuration to include a replicas option for managing concurrent sandbox containers.
- Improved logging and context management in SandboxMiddleware for better sandbox lifecycle handling.
- Enhanced network port allocation logic to bind to 0.0.0.0 for compatibility with Docker.
- Updated Docker Compose files to ensure proper volume management and environment variable configuration.
- Created scripts to ensure necessary configuration files are present before starting services.
- Cleaned up unused MCP server configurations in extensions_config.example.json.
* Address Copilot review suggestions from PR #1068 (#9)
---------
Co-authored-by: Copilot <198982749+Copilot@users.noreply.github.com>
* feat: add IM channels system for Feishu, Slack, and Telegram integration
Bridge external messaging platforms to DeerFlow via LangGraph Server with
async message bus, thread management, and per-channel configuration.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: address review comments on IM channels system
Fix topic_id handling in store remove/list_entries and manager commands,
correct Telegram reply threading, remove unused imports/variables, update
docstrings and docs to match implementation, and prevent config mutation.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* update skill creator
* fix im reply text
* fix comments
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* Add checkpointer configuration to config.example.yaml
- Introduced a new section for checkpointer configuration to enable state persistence for the embedded DeerFlowClient.
- Documented supported types: memory, sqlite, and postgres, along with examples for each.
- Clarified that the LangGraph Server manages its own state persistence separately.
* refactor(checkpointer): streamline checkpointer initialization and logging
* fix(uv.lock): update revision and add new wheel URLs for brotlicffi package
* feat: add langchain-anthropic dependency and update related configurations
* Fix checkpointer lifecycle, docstring, and path resolution bugs from PR #1005 review (#4)
* Initial plan
* Address all review suggestions from PR #1005
Co-authored-by: foreleven <4785594+foreleven@users.noreply.github.com>
* Fix resolve_path to always return real Path; move SQLite special-string handling to callers
Co-authored-by: foreleven <4785594+foreleven@users.noreply.github.com>
---------
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: foreleven <4785594+foreleven@users.noreply.github.com>
---------
Co-authored-by: Copilot <198982749+Copilot@users.noreply.github.com>
Co-authored-by: foreleven <4785594+foreleven@users.noreply.github.com>
* feat: Add reasoning effort configuration support
* Add `reasoning_effort` parameter to model config and agent initialization
* Support reasoning effort levels (minimal/low/medium/high) for Doubao/GPT-5 models
* Add UI controls in input box for reasoning effort selection
* Update doubao-seed-1.8 example config with reasoning effort support
Fixes & Cleanup:
* Ensure UTF-8 encoding for file operations
* Remove unused imports
* fix: set reasoning_effort to None for unsupported models
* fix: unit test error
* Update frontend/src/components/workspace/input-box.tsx
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* feat: add Novita AI as optional LLM provider
Adds Novita AI (https://novita.ai) as an optional, OpenAI-compatible
LLM provider.
Changes:
- Added Novita model configuration example in config.example.yaml
- Added NOVITA_API_KEY to .env.example
Usage: Set NOVITA_API_KEY in your environment and use novita-gpt-4
as the model name.
* update correct model info
* Update README.md
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* feat(subagents): make subagent timeout configurable via config.yaml
- Add SubagentsAppConfig supporting global and per-agent timeout_seconds
- Load subagents config section in AppConfig.from_file()
- Registry now applies config.yaml overrides without mutating builtin defaults
- Polling safety-net in task_tool is now dynamic (execution timeout + 60s buffer)
- Document subagents section in config.example.yaml
- Add make test command and enforce TDD policy in CLAUDE.md
- Add 38 unit tests covering config validation, timeout resolution, registry
override behavior, and polling timeout formula
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* feat(subagents): add logging for subagent timeout config and execution
- Log loaded timeout config (global default + per-agent overrides) on startup
- Log debug message in registry when config.yaml overrides a builtin timeout
- Include timeout in executor's async execution start log
- Log effective timeout and polling limit when a task is dispatched
- Fix UnboundLocalError: move max_poll_count assignment before logger.info
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* ci(backend): add lint step and run all unit tests via Makefile
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix lint
---------
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
* Adds Kubernetes sandbox provisioner support
* Improves Docker dev setup by standardizing host paths
Replaces hardcoded host paths with a configurable root directory,
making the development environment more portable and easier to use
across different machines. Automatically sets the root path if not
already defined, reducing manual setup steps.
* feat: adds docker-based dev environment
* docs: updates Docker command help
* fix local dev
* feat(sandbox): add Kubernetes-based sandbox provider for multi-instance support
* fix: skills path in k8s
* feat: add example config for k8s sandbox
* fix: docker config
* fix: load skills on docker dev
* feat: support sandbox execution to Kubernetes Deployment model
* chore: rename web service name
Add subagents.enabled flag in config.yaml to control subagent feature:
- When disabled, task/task_status tools are not loaded
- When disabled, system prompt excludes subagent documentation
- Default is enabled for backward compatibility
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add native Apple Container support for better performance on macOS while
maintaining full Docker compatibility. Enhance documentation with memory system
details, development guidelines, and sandbox setup instructions. Improve dev
experience with container image pre-pulling and unified cleanup tools.
Key changes:
- Auto-detect and prefer Apple Container on macOS with Docker fallback
- Add APPLE_CONTAINER.md with complete usage and troubleshooting guide
- Document memory system architecture in CLAUDE.md
- Add make setup-sandbox for pre-pulling container images
- Create cleanup-containers.sh for cross-runtime container cleanup
- Update all related documentation (README, SETUP, config examples)
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
- Add memory API endpoints for retrieving memory data:
- GET /api/memory - get current memory data
- POST /api/memory/reload - reload from file
- GET /api/memory/config - get memory configuration
- GET /api/memory/status - get config and data together
- Optimize MemoryMiddleware to only use user inputs and final
assistant responses, filtering out intermediate tool calls
- Add memory configuration example to config.example.yaml
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add model-aware vision tool loading based on supports_vision flag
- Move view_image_tool from config to builtin tools for dynamic inclusion
- Add timeout to image search to prevent hanging requests
- Optimize image search results format using thumbnails
- Add image validation for reference images in generation
- Improve error handling with detailed messages
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Add image viewing capability for vision-enabled models with ViewImageMiddleware and view_image_tool. Limit web_fetch tool output to 4096 characters to prevent excessive content. Update model config to support vision capability flag.
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
When using thinking-enabled models (like Kimi K2.5, DeepSeek), the API
expects reasoning_content on all assistant messages. The original
ChatDeepSeek stores reasoning_content in additional_kwargs but doesn't
include it when making subsequent API calls, causing "reasoning_content
is missing" errors.
This adds PatchedChatDeepSeek which overrides _get_request_payload to
restore reasoning_content from additional_kwargs into the payload.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add environment field to sandbox config for injecting env vars into container
- Support $VAR syntax to resolve values from host environment variables
- Refactor frontend API modules to use centralized getBackendBaseURL()
- Improve Doraemon skill with explicit input/output path arguments
- Add .env.example file
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add comprehensive MCP integration using langchain-mcp-adapters to enable
pluggable external tools from MCP servers.
Features:
- MCP server configuration via mcp_config.json
- Automatic lazy initialization for seamless use in both FastAPI and LangGraph Studio
- Support for multiple MCP servers (filesystem, postgres, github, brave-search, etc.)
- Environment variable resolution in configuration
- Tool caching mechanism for optimal performance
- Complete documentation and setup guide
Implementation:
- Add src/mcp module with client, tools, and cache components
- Integrate MCP config loading in AppConfig
- Update tool system to include MCP tools automatically
- Add eager initialization in FastAPI lifespan handler
- Add lazy initialization fallback for LangGraph Studio
Dependencies:
- Add langchain-mcp-adapters>=0.1.0
Documentation:
- Add MCP_SETUP.md with comprehensive setup guide
- Update CLAUDE.md with MCP system architecture
- Update config.example.yaml with MCP configuration notes
- Update README.md with MCP setup instructions
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Implement a skills framework that enables specialized workflows for
specific tasks (e.g., PDF processing, web page generation). Skills are
discovered from the skills/ directory and automatically mounted in
sandboxes with path mapping support.
- Add SkillsConfig for configuring skills path and container mount point
- Implement dynamic skill loading from SKILL.md files with YAML frontmatter
- Add path mapping in LocalSandbox to translate container paths to local paths
- Mount skills directory in AIO Docker sandbox containers
- Update lead agent prompt to dynamically inject available skills
- Add setup documentation and expand config.example.yaml
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
